'Signal model' presentation slideshows

Time Series Analysis in AFNI

1.33k views • 103 slides

Time Series Analysis in AFNI

1.03k views • 103 slides

Time Series Analysis in AFNI

1.21k views • 97 slides

Time Series Analysis in AFNI

1.06k views • 92 slides

Time Series Analysis in AFNI

1.06k views • 92 slides

Time Series Analysis in AFNI

920 views • 92 slides

Time Series Analysis in AFNI

922 views • 92 slides

Time Series Analysis in AFNI

Time Series Analysis in AFNI. Outline: 6+ Hours of Edification. Philosophy Sample FMRI data Theory underlying FMRI analyses: the HRF “Simple” or “Fixed Model” regression analysis Theory and Hands-on examples “Deconvolution” or “Variable Model” analysis Theory and Hands-on examples

1.04k views • 78 slides

Time Series Analysis in AFNI

908 views • 78 slides

BJT in Saturation Mode

BJT in Saturation Mode. Section 4.5. Schedule. Outline. Modes of Operations Review of BJT in the active Region BJT in Saturation Mode Digital Integrated Circuits. Modes of Operation. Applications: 1. Saturation and cut-off mode are used in digital circuits.

933 views • 46 slides

FMRI Data Modeling, the G eneral L inear M odel, and Statistical Inference

456 views • 45 slides

Bipolar Junction Transistors (BJT)

Bipolar Junction Transistors (BJT). NPN. PNP. BJT Cross-Sections. Emitter. Collector. NPN PNP. Common-Emitter NPN Transistor. Reverse bias the CBJ. Forward bias the BEJ. Input Characteristics. Plot I B as f(V BE , V CE )

655 views • 44 slides

Bipolar Junction Transistors (BJT)

Bipolar Junction Transistors (BJT). NPN. PNP. BJT Cross-Sections. Emitter. Collector. NPN PNP. Common-Emitter NPN Transistor. Reverse bias the CBJ. Forward bias the BEJ. Input Characteristics. Plot I B as f(V BE , V CE )

1.42k views • 44 slides

Outline: 6 + Hours of Edification

442 views • 36 slides

Project background

Laser characterization and modelling for the development of the Super LHC versatile transceiver Sergio Rui Silva Marie Curie Fellow PH-ESE-BE CERN 2 April 2009. Project background.

395 views • 30 slides

Generalized Sparse Signal Mixing Model and Application to Noisy Blind Source Separation

Generalized Sparse Signal Mixing Model and Application to Noisy Blind Source Separation. Justinian Rosca Christian Borss # Radu Balan. Siemens Corporate Research, Princeton, USA # Presently: University of Brawnschweig. s L-1. s 2. s 1. s L. n. x 1. x 2. x D. Signal Processor.

376 views • 24 slides

An Average of Several Sparse Representations is Better than the Sparsest One Alone

366 views • 24 slides

Sparse Reconstruction and Feature Extraction

367 views • 22 slides

Maximum-Likelihood Synchronization and Channel Estimation for OFDMA Uplink Transmissions

Maximum-Likelihood Synchronization and Channel Estimation for OFDMA Uplink Transmissions. Chi-En Li Directed by Prof. Jung-Shan Lin Graduate Institute of Communication Engineering National Chi Nan University 12/ 11/ 2008. Outline. System model and signal model CFO estimation

338 views • 18 slides

A F N I & S U M A Concepts, Principles, Demos

A F N I & S U M A Concepts, Principles, Demos. http://afni.nimh.nih.gov/afni. Some Goals of FMRI Analyses. Task-based experiments Per subject : estimate amplitude of BOLD response to each different type of stimulus

168 views • 16 slides